Design and Implementation of SEMAR IoT Server Platform with Applications

Abstract

Nowadays, rapid developments of Internet of Things (IoT) technologies have increased possibilities of realizing smart cities where collaborations and integrations of various IoT application systems are essential. However, IoT application systems have often been designed and deployed independently without considering the standards of devices, logics, and data communications. In this paper, we present the design and implementation of the IoT server platform called Smart Environmental Monitoring and Analytical in Real-Time (SEMAR) for integrating IoT application systems using standards. SEMAR offers Big Data environments with built-in functions for data aggregations, synchronizations, and classifications with machine learning. Moreover, plug-in functions can be easily implemented. Data from devices for different sensors can be accepted directly and through network connections, which will be used in real-time for user interfaces, text files, and access to other systems through Representational State Transfer Application Programming Interface (REST API) services. For evaluations of SEMAR, we implemented the platform and integrated five IoT application systems, namely, the air-conditioning guidance system, the fingerprint-based indoor localization system, the water quality monitoring system, the environment monitoring system, and the air quality monitoring system. When compared with existing research on IoT platforms, the proposed SEMAR IoT application server platform offers higher flexibility and interoperability with the functions for IoT device managements, data communications, decision making, synchronizations, and filters that can be easily integrated with external programs or IoT applications without changing the codes. The results confirm the effectiveness and efficiency of the proposal.

An Enhancement of Outdoor Location-Based Augmented Reality Anchor Precision through VSLAM and Google Street View

“…User interactions are managed by an event handler to display the AR object and Map View . Then, the SEMAR server [ 47 ] is used to store the AR content persistence data. The persistence data include the anchor ID, latitude, longitude, altitude, and heading values of the generated AR objects.…”

A Survey of AI Techniques in IoT Applications with Use Case Investigations in the Smart Environmental Monitoring and Analytics in Real-Time IoT Platform

“…In this section, we review the SEMAR IoT application server platform to facilitate the development of IoT applications in the cloud. In our previous studies [4], we presented the design and implementation of SEMAR with several IoT application systems. Currently, SEMAR provides integrated capabilities functions to collect, display, process, and analyze sensor data.…”

“…In the previous research, we introduced the concept of a drone-based building crack detection system [85]. This system consists of flying drones and edge devices connected to the SEMAR server.…”

“…It can serve as a cloud server for integrating various IoT application systems. It offers various integration capabilities for the collection, display, and analysis of sensor data on a single platform [4], by providing built-in functions for data communications, aggregations, synchronizations, and classifications using machine learning algorithms in Big Data environments. It also supports the implementation of plug-in functions by allowing other systems to access data through the Representational State Transfer Application Programming Interface (REST API).…”

Machine Learning Assists IoT Localization: A Review of Current Challenges and Future Trends

“…Panduman et al presented Smart Environmental Monitoring and Analytical in Real-Time (SEMAR), an IoT server platform. The SEMAR platform made use of an API to service various IoT applications, including localization [ 55 ].…”